ABSTRACT
The ongoing spillover of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) calls for expedited countermeasure through developing therapeutics from natural reservoirs and/or the use of less time-consuming drug discovery methodologies. This study aims to apply these approaches to identify potential blockers of the virus from the longstanding medicinal herb, Lagerstroemia speciosa, through comprehensive computational-based screening. Nineteen out of 22 L. speciosa phytochemicals were selected on the basis of their pharmacokinetic properties. SARS-CoV-2 Main protease (Mpro), RNA-directed RNA polymerase (RdRp), Envelope viroporin protein (Evp) and receptor-binding domain of Spike glycoprotein (S-RBD), as well as the human receptor Angiotensin-converting enzyme-2 (hACE2) were chosen as targets. The screening was performed by molecular docking, followed by 100-ns molecular dynamic simulations and free energy calculations. 24-Methylene cycloartanol acetate (24MCA) was found as the best inhibitor for both Evp and RdRp, and sitosterol acetate (SA) as the best hit for Mpro, S-RBD and hACE2. Dynamic simulations, binding mode analyses, free energy terms and share of key amino acids in protein-drug interactions confirmed the stable binding of these phytocompounds to the hotspot sites on the target proteins. With their possible multi-targeting capability, the introduced phytoligands might offer promising lead compounds for persistent fight with the rapidly evolving coronavirus. Therefore, experimental verification of their safety and efficacy is recommended.
ABSTRACT
Human norovirus (HuNoV) causes acute viral gastroenteritis in all age groups, and dehydration and severe diarrhea in the elderly. The World Health Organization reports â¼1.45 million deaths from acute gastroenteritis annually in the world. Rupintrivir, an inhibitory medicine against the human rhinovirus C3 protease, has been reported to inhibit HuNoV 3C protease. However, several HuNoV 3C protease mutations have been revealed to reduce the susceptibility of HuNoV to rupintrivir. The structural details behind rupintrivir-resistance of these single-point mutations (A105V and I109V) are not still clear. Hence, in this study, a combination of computational techniques were used to determine the rupintrivir-resistance mechanism and to propose an inhibitor against wild-type and mutant HuNoV 3C protease through structure-based virtual screening. Dynamic structural results indicated the unstable binding of rupintrivir at the cleft binding site of the wild-type and mutant 3C proteases, leading to its detachment. Our findings presented that the domain II of the HuNoV 3C protease had a critical role in binding of inhibitory molecules. Binding energy computations, steered molecular dynamics and umbrella sampling simulations confirmed that amentoflavone, the novel suggested inhibitor, strongly binds to the cleft site of all protease models and has a good structural stability in the complex system along the molecular dynamic simulations. Our in silico study proposed the selected compound as a potential inhibitor against the HuNoV 3C protease. However, additional experimental and clinical studies are required to corroborate the therapeutic efficacy of the compound.
Subject(s)
Antiviral Agents , Norovirus , Protease Inhibitors , Humans , Antiviral Agents/chemistry , Antiviral Agents/pharmacology , Gastroenteritis/drug therapy , Gastroenteritis/virology , Norovirus/drug effects , Norovirus/metabolism , Peptide Hydrolases , Protease Inhibitors/chemistry , Protease Inhibitors/pharmacology , Viral Proteins/antagonists & inhibitors , Viral Proteins/chemistryABSTRACT
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) expresses a multifunctional papain-like proteinase (PLpro), which mediates the processing of the viral replicase polyprotein. Inhibition of PLpro has been shown to suppress the viral replication. This study aimed to explore new anti-PLpro candidates by applying virtual screening based on GRL0617, a known PLpro inhibitor of SARS coronavirus (SARS-CoV). The three-dimensional (3D) structure of SARS-CoV-2 PLpro was built by homology modeling, using SARS-CoV PLpro as the template. The model was refined and studied through molecular dynamic simulation. AutoDock Vina was then used to perform virtual screening where 50 chemicals with at least 65% similarity to GRL0617 were docked with the optimized SARS-CoV-2 PLpro. In this screening, 5-(aminomethyl)-2-methyl-N-[(1R)-1-naphthalen-1-ylethyl]benzamide outperformed GRL0617 in terms of binding affinity (-9.7 kcal/mol). Furthermore, 2-(4-fluorobenzyl)-5-nitro-1H-isoindole-1,3(2H)-dione (previously introduced as an inhibitor of cyclooxygenase-2), 3-nitro-N-[(1r)-1-phenylethyl]-5-(trifluoromethyl)benzamide (inhibitor against Mycobacterium tuberculosis), as well as the recently introduced SARS-CoV-2 PLpro inhibitor 5-acetamido-2-methyl-N-[(1S)-1-naphthalen-1-ylethyl]benzamide showed promising affinity for the viral proteinase. All of the identified compounds demonstrated an acceptable pharmacokinetic profile. In conclusion, our findings represent rediscovery of analgesic, anti-inflammatory, antibacterial, or antiviral drugs as promising pharmaceutical candidates against the ongoing coronavirus.
Subject(s)
Antiviral Agents/pharmacology , Coronavirus 3C Proteases/antagonists & inhibitors , Coronavirus 3C Proteases/chemistry , Protease Inhibitors/pharmacology , Antiviral Agents/adverse effects , Antiviral Agents/chemistry , Antiviral Agents/pharmacokinetics , Binding Sites , Chemical and Drug Induced Liver Injury/etiology , Computer Simulation , Coronavirus 3C Proteases/genetics , Coronavirus 3C Proteases/metabolism , Drug Evaluation, Preclinical/methods , Humans , Microsomes, Liver/drug effects , Molecular Docking Simulation , Molecular Dynamics Simulation , Protease Inhibitors/adverse effects , Protease Inhibitors/chemistry , Protease Inhibitors/pharmacokinetics , Protein Conformation , Structure-Activity RelationshipABSTRACT
Coronavirus disease 2019 (COVID-19) is an acute pneumonic disease, with no prophylactic or specific therapeutical solution. Effective and rapid countermeasure against the spread of the disease's associated virus, SARS-CoV-2, requires to incorporate the computational approach. In this study, we employed various immunoinformatics tools to design a multi-epitope vaccine polypeptide with the highest potential for activating the human immune system against SARS-CoV-2. The initial epitope set was extracted from the whole set of viral structural proteins. Potential non-toxic and non-allergenic T-cell and B-cell binding and cytokine inducing epitopes were then identified through a priori prediction. Selected epitopes were bound to each other with appropriate linkers, followed by appending a suitable adjuvant to increase the immunogenicity of the vaccine polypeptide. Molecular modelling of the 3D structure of the vaccine construct, docking, molecular dynamics simulations and free energy calculations confirmed that the vaccine peptide had high affinity for Toll-like receptor 3 binding, and that the vaccine-receptor complex was highly stable. As our vaccine polypeptide design captures the advantages of structural epitopes and simultaneously integrates precautions to avoid relevant side effects, it is suggested to be promising for elicitation of an effective and safe immune response against SARS-CoV-2 in vivo.